The course will enable the students to
Course Outcomes (COs).
Course Outcome (at course level) | Learning and teaching strategies | Assessment Strategies |
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On completion of this course, the students will: CO152. describe the nature and scope of econometrics. CO153. examine various statistical tools like probability distributions used in econometrics. CO154. comprehend the estimation and inference of simple and multiple linear regression models and functional forms. CO155. know about the techniques of verification of economic theories and laws. CO156. come to get trained about how the research is conducted. | Approach in teaching: Interactive Lectures and Discussions.
Learning activities for the students: Practice Modules and Assignments. | Class activity, Assignments and Semester end examinations. |
Nature of Econometrics and Statistical Concepts Nature, scope and methodology of econometrics;
Statistical concepts: Normal distribution; chi-square, t- and F-distributions; estimation of parameters; properties of estimators; testing of hypotheses: defining statistical hypotheses Type I and Type II errors; power of a test.
Simple Linear Regression Model: Two Variable Case-I Nature of regression analysis; assumptions of Classical Linear Regression Model, estimation of model by method of ordinary least squares; properties of least square estimators; Gauss-Markov theorem.
Simple Linear Regression Model: Two Variable Case-II Goodness of fit; tests of hypotheses; scaling and units of measurement; confidence intervals; Chow Test, forecasting.
Functional forms of regression models Log-linear model, semilog models, reciprocal models and logarithmic reciprocal model.
Multiple Linear Regression Model Estimation of parameters; properties of OLS estimators; partial regression coefficients; goodness of fit - R2 and adjusted R 2; testing hypotheses – individual and joint.
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